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Publicly Available Published by De Gruyter Mouton November 4, 2010

Does prosodic constituency signal relative predictability? A Smooth Signal Redundancy hypothesis

Alice Turk
From the journal Laboratory Phonology


This paper explores issues relating to signaling word boundaries from the perspective of Aylett's Smooth Signal Redundancy proposal (Aylett, Stochastic suprasegmentals: Relationships between redundancy, prosodic structure and care of articulation in spontaneous speech, University of Edinburgh, 2000, Aylett and Turk, Language and Speech 47: 31–56, 2004) that language has evolved to spread redundancy, i.e. recognition likelihood, evenly throughout utterances. In Aylett's proposal, information that enables listeners to identify sequences of elements in an utterance (signal redundancy) comes from two sources: a) language redundancy, recognition likelihood based on lexical, syntactic, semantic, pragmatic and other factors, and b) acoustic redundancy, recognition likelihood based on acoustic salience. Smooth signal redundancy is achieved by a complementary relationship between language redundancy and acoustic redundancy that is implemented via prosodic structure.

While Aylett and Turk (Language and Speech 47: 31–56, 2004) present the case for prosodic prominence as a lever for modulating the acoustic salience of syllables, the current paper proposes that prosodic constituency also fulfils this function for words. The current paper proposes that the signal redundancy, or recognition likelihood, of words can be manipulated by signaling their boundaries, and that the occurrence and strength of these boundary markers correlates inversely with language redundancy. Prosodic constituency implements the complementary relationship between language redundancy and word boundary salience.

Smooth Signal Redundancy provides an integrated explanation for a set of properties relating to prosodic constituent structure.

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Published Online: 2010-11-4
Published in Print: 2010-10-1

© 2010 Walter de Gruyter GmbH & Co. KG, Berlin/New York

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